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Correlation
Published in Marcello Pagano, Kimberlee Gauvreau, Heather Mattie, Principles of Biostatistics, 2022
Marcello Pagano, Kimberlee Gauvreau, Heather Mattie
The Spearman rank correlation coefficient may also be thought of as a measure of the concordance of the ranks for the outcomes x and y. If the 20 measurements of percent immunization against dpt and under-5 mortality rate in Table 16.2 happened to be ranked in the same order for each variable – meaning that the country with the ith largest percent immunization also has the ith largest mortality rate for all values of i – then each difference di would be equal to 0, and
A Corpus Based Quantitative Analysis of Gurmukhi Script
Published in Ayodeji Olalekan Salau, Shruti Jain, Meenakshi Sood, Computational Intelligence and Data Sciences, 2022
Gurjot Singh Mahi, Amandeep Verma
is the difference between two rankings, which can be written as , where is the rank. Following the Pearson correlation coefficient, Spearman rank correlation values tend to range between , i.e., . Similarly, is the number of values in the dataset.
Data evaluation
Published in Robyn L. Tate, Michael Perdices, Single-Case Experimental Designs for Clinical Research and Neurorehabilitation Settings, 2019
Robyn L. Tate, Michael Perdices
Tau-U is analogous to Kendall’s Rank Correlation Coefficient and the Mann–Whitney U tests. Like Non-overlap of All Pairs (NAP), it is based on comparison of overlap in all data pairs, but in addition to percentage of non-overlap, also takes into account the percentage of overlap in the data. Like SMTL, Tau-U is the only other non-overlap method that combines non-overlap and trend to control for effects of ‘improving’ trend (whether linear, curvilinear, or mixed) in the baseline. It is fairly impervious to confounding effects of autocorrelation (Parker et al., 2011b) and reliably detects medium-size effects in short data sets (Parker et al., 2014). Vannest and Ninci (2015, p. 408) suggest the following guide for interpreting ESs generated by Tau-U: “A 0.20 improvement may be considered a small change, 0.2 to 0.60 a moderate change, 0.60 to 0.80 a large change and above 0.80 a large to very large change, depending on the context.” Moreover, it has good statistical power and a known sampling distribution (same as that of Kendall’s Rank Correlation Coefficient), hence p-values and confidence intervals can be calculated, and Tau-U can be used in meta-analytic studies. The online calculator11 available for TAU-U can check for trend in the baseline, adjust for it when necessary, and compute contrasts between individual phase pairs (i.e. A vs B), as well as omnibus statistics.
Objective assessment of eyelid position and tear meniscus in facial nerve palsy
Published in Orbit, 2022
Alicia Galindo-Ferreiro, Victoria Marqués-Fernández, Hortensia Sanchez-Tocino, Silvana A. Schellini
Data were transferred to an Access spreadsheet (Microsoft Corp., Redmond, WA, USA) for statistical analysis. Univariate analysis was performed using Statistical Package for Social Sciences (SPSS 24; IBM Corp., New York, NY, USA). The Shapiro–Wilk test was used to assess the distribution of data. Descriptive statistics were calculated such as the mean ± standard deviation or median and interquartile range (IQR) values. If there was no normal distribution of data, the frequencies and percentage proportions were calculated for qualitative variables. Nonparametric analysis for related samples was performed for statistical validation. For multiple continuous variables that were not normally distributed, the Kruskal Wallis and U de Mann–Whitney p-value were calculated for validation of intergroup and intragroup differences, respectively. Spearman’s rank correlation coefficient was used to evaluate the relationship between variables. A P-value less than 0.05 was considered statistically significant.
An overview of heavy-tail extensions of multivariate Gaussian distribution and their relations
Published in Journal of Applied Statistics, 2022
A density function is not often tractable or not known a priori, but we can still achieve legitimate estimates for the scatter matrix parameter et al. [32] proved that the Kendall's tau estimator is invariant to the choice of R, and thus can be used to detect the correlation structure of any EL-distributed data. The gist of Kendall's tau estimator, or the rank correlation, is that it solely depends on the rank of samples, not the magnitude, thereby bypassing estimation of the scalar random variable R. Recall its definition where the ith entry of
Association between IL-37 and Systemic Lupus Erythematosus Risk
Published in Immunological Investigations, 2022
Qian Wu, Jie Zhou, Zhi-Chao Yuan, You-Yu Lan, Wang-Dong Xu, An-Fang Huang
Association of IL-37 expression and different clinical laboratory features was analyzed according to the Wilcoxon rank-sum test. Spearman’s rank correlation evaluated relationship between two variables. Numerical data were designed as mean (±SD) or median (interquartile range) according to normality test. Power analysis was carried out by Power and Sample Size Calculation software. Genotype frequencies for IL37 SNPs were determined by Hardy–Weinberg equilibrium (HWE). Differences in genotypes and allelic distribution between SLE and controls were tested by χ2 test or Fisher’s exact test. Nonconditional logistic analysis calculated odds ratios (ORs) and 95% confidence interval (CI). For multiple comparisons, bonferroni correction was carried out. HaploView 4.1 software selected tagSNP and analyzed linkage disequilibrium (Zhang et al. 2020, 2018). IL37 haplotypes were assessed by online software SHEsis. Statistical analyses were performed by SPSS software (Version 23.0, Chicago) and GraphPad Prism (Version 5.01).